A deep learning-based surrogate model for trans-dimensional inversion of discrete fracture networks-Reference-Cited by-同舟云学术

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A deep learning-based surrogate model for trans-dimensional inversion of discrete fracture networks

Published:2024-07 Issue: Volume:638 Page:131524
ISSN:0022-1694
Container-title:Journal of Hydrology
language:en
Short-container-title:Journal of Hydrology

Author:

Feng Runhai,Nasser Saleh

Publisher

Elsevier BV

Reference39 articles.

1. ADFNE: Open source software for discrete fracture network engineering, two and three dimensional applications;Alghalandis;Comput. Geosci.,2017

2. Fracture network characterization with deep generative model based stochastic inversion;Chen;Energy,2023

3. A two-stage downscaling hydrological modeling approach via convolutional conditional neural process and geostatistical bias correction;Cui;J. Hydrol.,2023

4. Efficient trans-dimensional Bayesian inversion for geoacoustic profile estimation;Dosso;Inverse Prob.,2014

5. Ensemble smoother with multiple data assimilation;Emerick;Comput. Geosci.,2013

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